Duration: 5-6 months

Data Science with Python

Real-time learning of Data Science with Python. Weekends only.

Course highlights:

• Session 1:
• Why Data Science, what is the market, what companies are looking for? (1%)
• Data science overview (2%)
• Data Analytics overview (2%)
• Python environment set up, installations of IDE (5%)
• Python learning from basics to advance (30%)
• Session 2  (10%):
  • Introduction to Business Analytics
  • Business Analytics and Competitive Advantage
  • Business Data & Systems
  • Data Lifecycle (DLC) & Data Quality
• Session 3 (10%): Descriptive Analytics – Part 1
  • Introduction to R and Working with Data in R
  • Exploratory Data Analytics
  • Measures of Central Tendency and Variation
  • Exercise on Data Quality
• Session 4 (10%): Descriptive Analytics – Part 2 & 3
  • Associative Data Analytics (Correlation and Association)
  • Strategic Data Acquisition for Analytics
  • Inferential Data Analytics (T-Test, A/B Testing, & ANOVA)
• Session 5 (10%): Predictive Analytics & Machine Learning
  • Fundamentals of Predictive Analytics
  • Regression Models – Simple Linear Regression and Multiple Linear Regression
  • Fundamentals of ML (Machine Learning)
  • Supervised & Unsupervised ML Algorithms
  • Exercise on Multiple Linear Regression (MLR)
• Session 6 (10%): Prescriptive Analytics & Data Products
  • Introduction to Prescriptive Analytics
  • Applying Prescriptive Analytics Techniques for Optimal Results
  • Data Products
  • Times-series data and Fast Fourier Transform (FFT) Analysis
  • Text Analytics in Enterprises
  • Good Analytics v/s Bad Analytics
• Session 7 (10%): Data Visualization & Wrap-up
  • Dashboards & Reports
  • Overview of Data Visualization
  • Data Visualization principles of Edward Tufte
  • 6 building blocks of Data Storytelling including Gestalt Principles
  • Managing your careers in Data Analytics
  • Wrap-up
• Object-Oriented Programming Concepts
• Operating Systems and Networks
• Types of software development models
• Rapid Application Development for OOSD
• Security for Developers
• Web Application Development
• Database Development
• .NET Web Applications
• Open Source Web Applications
• Object-Oriented Practicum
• Threaded Project for OOSD
• Software Project Concepts

Session 2: Practicum 2 months (Would get you more details)

Note: We will help you install all tools and applications for your practice

Fees: Coming soon

Pre-Requisites: Previous software development and/or BA and/ or QA training or experience would help

How to join this course:

• Register with your name, email address, and $100 registration fees HERE (We only take students who are registered, paid registration fees, and committed to this course. Registration fees are not refundable however we may return only if IOFIT cancel the course)

What is next? REGISTRATION.